Fernando Suárez

1.5k citations
27 papers · 596 · h-index 11

Impact in

Papers in

    • Biomedical Text Mining and Ontologies 4
    • Epigenetics and DNA Methylation 3
    • RNA modifications and cancer 3
    • Acute Myeloid Leukemia Research 6

Fernando Suárez

26 papers receiving 586 citations

Peers

Fernando Suárez
Comparison fields: 5 of 92
  • Health Informatics 22
  • Cancer Research 165
  • Hematology 79
  • Molecular Biology 377
  • Cell Biology 68
Replace Tai‐Chung Huang with:
Tai‐Chung Huang Taiwan
Yuriko Mori Germany
David Mysona United States
Russell R. Braeuer United States
Ulrich Tschulena Germany
Mousheng Xu United States
Fábio Pittella Silva Brazil
Bartlomiej Bartkowiak United States
Hyun Jeong Kim South Korea
Fernando Suárez relative to Tai‐Chung Huang Taiwan Tai‐Chung Huang's profile →
Citations per field
00.5×2.8×
Tai‐Chung Huang · 1×
Citations per year

Countries citing papers authored by Fernando Suárez

Since Specialization
Citations

This map shows the geographic impact of Fernando Suárez's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Fernando Suárez with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fernando Suárez more than expected).

Fields of papers citing papers by Fernando Suárez

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Fernando Suárez. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Fernando Suárez. The network helps show where Fernando Suárez may publish in the future.

Co-authors

The 25 scholars most cited alongside Fernando Suárez, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Fernando Suárez Line = papers co-authored together Fernando Suárez links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2008158
2 201275
3 201056
4 200553
5 200845
6 201038
7 201731
8 200824
9 200723
10 202221
11 202313
12 20079
13 20197
14 20217
15
Análisis clínico epidemiológico de factores asociados a malformaciones congénitas ECLAMC - Hospital Universitario San Ignacio junio-diciembre de 2001
20016
16 20186
17 20235
18 20054
19 20083
20 20183

About Fernando Suárez

Fernando Suárez is a scholar working on Molecular Biology, Hematology, Health Informatics, Genetics and Cancer Research, having authored 27 papers that have together received 596 indexed citations. Recurring topics across this work include Acute Myeloid Leukemia Research (6 papers), Artificial Intelligence in Healthcare and Education (5 papers), Biomedical Text Mining and Ontologies (4 papers), Epigenetics and DNA Methylation (3 papers), RNA modifications and cancer (3 papers), Reconstructive Facial Surgery Techniques (2 papers), Acute Lymphoblastic Leukemia research (2 papers) and Genetic Syndromes and Imprinting (2 papers). The work is most often cited by research in Health Informatics (22 citations), Cancer Research (165 citations), Hematology (79 citations), Molecular Biology (377 citations) and Cell Biology (68 citations). Fernando Suárez has collaborated with scholars based in Canada, United States and India. Frequent co-authors include Mark D. Minden, Aaron D. Schimmer, Shadi Dalili, Marcela Gronda, Rose Hurren, Tabitha E. Wood, Craig D. Simpson, Robert A. Batey, Xinliang Mao and Yanina Eberhard. Their work appears in journals such as Blood, Journal of Clinical Oncology, Molecular Cancer Therapeutics, JCO Clinical Cancer Informatics and Molecular Cell.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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